Job Description Parser

Extract structured JSON from any job description in seconds using AI. Paste any job posting — from LinkedIn, Indeed, or anywhere else — and get back clean, validated data every time.

What it does

Job Description Parser uses AI to extract key information from job postings. No regex, no brittle parsing rules. It handles messy real-world job descriptions including boilerplate, noise, and non-standard formatting.

Input: Raw job description text (paste from any source)

Output: Structured JSON with 16 fields

Extracted fields

• 📋 Job title — exact role name
• 🏢 Company — hiring organization
• 📍 Location — city, state, country
• 🏠 Remote policy — remote, hybrid, or onsite
• ⏰ Employment type — full-time, part-time, or contract
• 📊 Seniority level — entry, mid, senior, lead, or executive
• 💰 Salary min/max — numeric values with currency
• 🛠️ Required skills — must-have competencies
• ⭐ Preferred skills — nice-to-have competencies
• 💻 Tech stack — specific technologies mentioned
• 📅 Years of experience — minimum required
• 🎓 Education required — degree or equivalent
• 🎁 Benefits — perks and benefits listed
• ✈️ Visa sponsorship — true, false, or null

How to use it

1. Open the Actor and click Start
2. Paste the full text of any job description into the Job Description field
3. Click Run
4. Find your structured JSON in the Output tab

The Actor works with any job description format — LinkedIn postings, Indeed listings, raw copy-pasted text, postings with boilerplate and equal opportunity statements included. The AI strips irrelevant content and returns only structured signal.

Sample output

{
  "job_title": "Senior Python Engineer",
  "company": "Acme Corp",
  "location": "New York, NY",
  "remote_policy": "hybrid",
  "employment_type": "full-time",
  "seniority": "senior",
  "salary_min": 140000,
  "salary_max": 180000,
  "salary_currency": "USD",
  "required_skills": ["Python", "AWS", "Docker", "FastAPI"],
  "preferred_skills": ["Kubernetes", "Terraform"],
  "tech_stack": ["Python", "AWS", "Docker", "FastAPI", "PostgreSQL"],
  "years_experience_min": 5,
  "education_required": null,
  "benefits": ["Health insurance", "401k", "Unlimited PTO"],
  "visa_sponsorship": null
}

Use cases

• ATS and recruiting tools — enrich job data automatically
• Job aggregator platforms — normalize listings from multiple sources
• HR automation workflows — parse postings in n8n, Make, or Zapier
• Salary benchmarking — extract compensation data at scale
• Labor market analytics — build datasets from job postings
• Resume matching — extract requirements to compare against candidate profiles

Built for automation

This Actor integrates naturally into Apify schedules, n8n workflows, Make scenarios, and custom pipelines via the Apify API. Feed it a job description, get back structured data, use it wherever you need it.

Reliability

• AI-powered extraction — not keyword matching
• Automatic retry with model escalation on parse failures
• Prompt injection resistant — tested against common attack patterns
• Handles long, noisy, boilerplate-heavy job descriptions
• Returns null for missing fields rather than guessing